Code changes to add PluggableDevice support for Inference

[rjauhari2]

Enable TF_LoadPluggableDeviceLibrary API for PluggableDevices

[Craigacp]

Adding this line should have generated more code which needs to be checked in, and we've had issues with the experimental C API in the past. Does this build correctly?

[rjauhari2]

Hi @Craigacp, I have added the code generated form c_api_experimental.h file. Yes, I was able to build it successfully. I have also tested loading our plugin solution, and tried running few models.

[karllessard]

I also recall trying to enable this experimental API in the past and we were facing compilation issues, maybe it has been cleaned up? But if it now works, that's amazing! I'll run a full build on all supported platforms before merging

[karllessard]

The standard (quick) build is failing. It looks like the symbols that are coming from the experimental layer are not present in the TensorFlow binaries we compile with (tensorflow_cc).

No wait I was wrong, what is missing is the generated classes under this package. @rjauhari2 , can you please commit them as well? It complains about three missing classes: TF_AttrBuilder, TF_ShapeAndTypeList and TF_CheckpointReader

Also, what command did you run to compile it successfully and what's your platform?

[rjauhari2]

Hi @karllessard, I used "mvn clean install -Pgenerating" command to build TF-Java. I have tested this on "linux-x86_64" machine. Now, I have added the generated class in "c_api" folder. With these changes I am able to build with "mvn clean install". Thanks for your review and guidance.

[karllessard]

Thanks a lot @rjauhari2. Unfortunately, the build failed on Windows, similar to what we've been observing in the past. We'll have to debug this on our side (unless you have access to a Windows machine), so we might want to push changes to your branch. To be continued...

[rjauhari2]

Thanks for your quick response. I am able to reproduce the error in your CI (GitHub actions). We shall try from our side.