我正在关注tutorial https://www.youtube.com/watch?v=T_afaArR0E8用于使用tensorflow services部署inception模型。我使用的是ubuntu 16.04和bazel 13.0。服务器正在运行,我能够ping通服务器。但是当我上传图片时,它显示以下错误
jennings@Jennings:~/serving$ bazel-bin/tensorflow_serving/example/inception_clie nt --server=localhost:9000 --image=./Xiang_Xiang_panda.jpg
Traceback (most recent call last):
File "/home/jennings/serving/bazel-bin/tensorflow_serving/example/inception_client.runfiles/tf_serving/tensorflow_serving/example/inception_client.py", line 56, in <module>
tf.app.run()
File "/home/jennings/serving/bazel-bin/tensorflow_serving/example/inception_client.runfiles/org_tensorflow/tensorflow/python/platform/app.py", line 125, in run
_sys.exit(main(argv))
File "/home/jennings/serving/bazel-bin/tensorflow_serving/example/inception_client.runfiles/tf_serving/tensorflow_serving/example/inception_client.py", line 51, in main
result = stub.Predict(request, 10.0) # 10 secs timeout
File "/home/jennings/.local/lib/python2.7/site-packages/grpc/beta/_client_adaptations.py", line 309, in __call__
self._request_serializer, self._response_deserializer)
File "/home/jennings/.local/lib/python2.7/site-packages/grpc/beta/_client_adaptations.py", line 195, in _blocking_unary_unary
raise _abortion_error(rpc_error_call)
grpc.framework.interfaces.face.face.ExpirationError: ExpirationError(code=StatusCode.DEADLINE_EXCEEDED, details="Deadline Exceeded")
当张量流服务客户端无法与服务器进行通信时,就会发生这种情况。或者这也可能是由于网络错误而发生的。如果您使用docker来托管tensorflow模型服务器,则需要在容器中打开端口,如下所述,
docker run --name=tensorflow_container -p 9020:9020 -it $USER/tensorflow-serving-devel
让我知道这是否有效。祝你好运。
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