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This image without gpu tensorflow/serving:2.10.0 can work fine in kubernetes. But when I change to a gpu image souce with FROM tensorflow/serving:2.10.0-gpu, it does't work, and raise expcetion File system scheme 'hdfs' not implemented.
HDFS file system scheme is moved to tensonflow-io. You only need to install tensorflow-io pip package and do the import tensorflow_io as tfio. There’s no need for any other code change as the filesystem plugin would be loaded behind the scenes.
Alternatively, export TF_USE_MODULAR_FILESYSTEM=1 in all hosts/envs that need to access hdfs should work.
In your case, since you are trying to build an image manually, you can follow Serving TensorFlow models with custom ops guide to create custom TF Serving with tensorflow-io support.
OS version: CentOS7
tfserving version: tensorflow/serving:2.10.0-gpu
kube version: v1.27.1
containerd version: v1.6.6
I am trying to run tfserving in a bare-metal kubernetes cluster.
Since the official did not provide an image with hdfs, I try to build a image manually.
Here is the Dockerfile:
This image without gpu
tensorflow/serving:2.10.0
can work fine in kubernetes. But when I change to a gpu image souce withFROM tensorflow/serving:2.10.0-gpu
, it does't work, and raise expcetionFile system scheme 'hdfs' not implemented
.I refer to the Dockerfile: https://github.com/tensorflow/serving/blob/master/tensorflow_serving/tools/docker/Dockerfile.gpu, but can not figure out the issue.
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