On Mon, Mar 20, 2017 at 3:41 AM, <ch.schnei...@gmail.com> wrote:

> I'm evaluating tensorflow serving which uses grpc to provide prediction
> endpoints to tensorflow clients. I managed to export a tensorflow model to
> serving and also to compile the protos for the client but I cannot get them
> to match up, getting the following error:
>
> AbortionError: AbortionError(code=StatusCode.INVALID_ARGUMENT,
> details="input tensor alias not found in signature: MY_ALIAS")
>

This is a gRPC-level error for an application-level (TensorFlow-level)
error; something the TensorFlow folks *might* want to do is catch this in
your client-side code and, by raising a TensorFlow-level exception instead,
make it look more TensorFlow-y and less gRPC-y. Then again it may not be
worth it, since it's describing a programming mistake and programming
mistakes should be fixed rather than made to look pretty.

Is there a way to query a grpc endpoint on what it actually provides,
> something like an index where the server says, this is what I know and this
> is what you need to give me?
>

You're roughly describing server reflection
<https://github.com/grpc/grpc/issues/2565>, which is coming
<https://github.com/grpc/grpc/pull/10216>, but which may not describe
services in sufficient detail to address your problem (it will describe
RPCs as requiring requests to be of a certain protocol buffer message type
but I don't think it will support saying things like "well this field needs
to be only positive integers and this other field must be set if this third
field is unset"). I think the error you're seeing is server-side TensorFlow
code telling you that you've made a TensorFlow-level mistake and trying to
describe the mistake to you (although the status details string it's giving
you is pretty short).
-Nathaniel

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